Triple

T35809227
Position Surface form Disambiguated ID Type / Status
Subject Main Event Mafia E1035182 entity
Predicate hasMember P10 FINISHED
Object Jenna Morasca
Jenna Morasca is an American reality television personality and professional wrestler best known for winning Survivor: The Amazon and her later appearances in TNA Wrestling.
E2194872 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Jenna Morasca | Statement: [Main Event Mafia, hasMember, Jenna Morasca]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jenna Morasca
Triple: [Main Event Mafia, hasMember, Jenna Morasca]
Generated description
Jenna Morasca is an American reality television personality and professional wrestler best known for winning Survivor: The Amazon and her later appearances in TNA Wrestling.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f76e1762408190b885a8456862e372 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a8d99eb481908dafe92649880c5a completed May 3, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20aae188819093007ca7be8ce211 completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a2108705081908bc39b9bba5c71bf completed June 23, 2026, 6 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3390427081909ddf30ecbcf6ab72 completed June 23, 2026, 7:19 a.m.
Created at: May 3, 2026, 4:06 p.m.